A storage server allows users to efficiently retrieve information from large volumes of data stored on a plurality of disks. For example, a video-on-demand server is a storage server that accepts user requests to view a particular movie from a video library, retrieves the requested program from disk, and delivers the program to the appropriate user(s). In order to provide high performance, storage servers may employ a plurality of processors connected to the disks, allowing the server to service multiple user requests simultaneously. In such multi-processor servers, processors issue commands to any of the disks, and a multi-port switch connecting the processors to the disks routes these commands to the appropriate disk. Data retrieved from disk is similarly routed back to the appropriate processor via the switch. Such servers use non-deterministic data routing channels for routing data. To facilitate accurate data retrieval, these channels require a sub-system to arbitrate conflicts that arise during data routing.
There are a number of problems, however, associated with such multi-processor servers. First, the switch becomes a major source of latency. Since all data exchanged between the processors and disks pass through the switch and the data must be correctly routed to the appropriate destination, certain overhead processes must be accomplished to arbitrate routing conflicts and handle command and control issues. These overhead requirements cause a delay in data routing that produces data delivery latency. While it is possible to reduce such latency by reserving extra channel bandwidth, this approach dramatically increases the cost of the server. Second, the server is required to store all user requested data in a cache prior to delivery. Such a caching technique leads to poor cache efficiency wherein multiple copies of the same user data is stored in cache. These problems can significantly degrade the disk bandwidth and performance provided by the server, thereby limiting the number of users that can be supported by a given number of processors and disks. In commercial applications such as video-on-demand servers, however, it is imperative to maximize the number of users that can be supported by the server in order to achieve a reasonable cost-per-user such that the servers are economically viable.
Therefore, there is a need in the art for a multi-processor storage server that can service multiple access requests simultaneously, while avoiding the congestion, overhead, and disk scheduling bottlenecks that plague current systems.